Pub Date : 2024-07-16DOI: 10.34190/ejbrm.22.2.3279
Ahmed M. Asfahani, Dina Dahlan, Maysaa Alnajem
In the evolving landscape of digital leadership and remote work, methodological challenges, particularly endogeneity, have emerged as significant concerns. Endogeneity, which arises when independent variables correlate with regression error terms, can introduce biases that compromise the validity of research findings. This systematic review examines the methodological underpinnings of research in digital leadership and remote work, focusing on how studies have addressed or overlooked the challenges posed by endogeneity. Drawing from 45 seminal articles published between 2019 and 2023, the review reveals a predominant preference for quantitative approaches, with a subset exploring qualitative narratives. While 15 studies directly tackled endogeneity using rigorous methodologies, 10 did not address it, indicating potential gaps in their investigative rigor. This study not only provides clarity and direction for future research endeavors but also supports the advancement of research methodology in business and management by emphasizing the need for methodological rigor in the study of digital leadership and remote work dynamics. By systematically evaluating the methods used to address endogeneity, this research advances the field of business and management research methodology by identifying best practices and highlighting areas for improvement. Specifically, it advocates for the adoption of advanced econometric techniques, such as instrumental variables and fixed effects models, to mitigate biases and enhance the reliability of research outcomes. Furthermore, this review underscores the importance of integrating both quantitative and qualitative approaches to capture the multifaceted nature of digital leadership and remote work, thereby contributing to a more comprehensive understanding of these domains. The study also highlights the influence of unobserved factors on outcomes such as employee productivity, leadership effectiveness, and team cohesiveness. In sum, this research provides a foundational framework for scholars aiming to enhance the robustness and validity of their studies in digital leadership and remote work, aligning with the broader goals of advancing research methodologies in business and management.
{"title":"Unraveling Endogeneity: A Systematic Review of Methodologies in Digital Leadership and Remote Work Research","authors":"Ahmed M. Asfahani, Dina Dahlan, Maysaa Alnajem","doi":"10.34190/ejbrm.22.2.3279","DOIUrl":"https://doi.org/10.34190/ejbrm.22.2.3279","url":null,"abstract":"In the evolving landscape of digital leadership and remote work, methodological challenges, particularly endogeneity, have emerged as significant concerns. Endogeneity, which arises when independent variables correlate with regression error terms, can introduce biases that compromise the validity of research findings. This systematic review examines the methodological underpinnings of research in digital leadership and remote work, focusing on how studies have addressed or overlooked the challenges posed by endogeneity. Drawing from 45 seminal articles published between 2019 and 2023, the review reveals a predominant preference for quantitative approaches, with a subset exploring qualitative narratives. While 15 studies directly tackled endogeneity using rigorous methodologies, 10 did not address it, indicating potential gaps in their investigative rigor. This study not only provides clarity and direction for future research endeavors but also supports the advancement of research methodology in business and management by emphasizing the need for methodological rigor in the study of digital leadership and remote work dynamics. By systematically evaluating the methods used to address endogeneity, this research advances the field of business and management research methodology by identifying best practices and highlighting areas for improvement. Specifically, it advocates for the adoption of advanced econometric techniques, such as instrumental variables and fixed effects models, to mitigate biases and enhance the reliability of research outcomes. Furthermore, this review underscores the importance of integrating both quantitative and qualitative approaches to capture the multifaceted nature of digital leadership and remote work, thereby contributing to a more comprehensive understanding of these domains. The study also highlights the influence of unobserved factors on outcomes such as employee productivity, leadership effectiveness, and team cohesiveness. In sum, this research provides a foundational framework for scholars aiming to enhance the robustness and validity of their studies in digital leadership and remote work, aligning with the broader goals of advancing research methodologies in business and management.","PeriodicalId":38532,"journal":{"name":"Electronic Journal of Business Research Methods","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141642937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-21DOI: 10.34190/ejbrm.22.1.3320
W. Kucharska, A. Kopytko
There is no learning without mistakes. However, there is a clash between ‘positive attitudes and beliefs’ regarding learning processes and the ‘negative attitudes and beliefs’ toward these being accompanied by mistakes. This clash exposes a cognitive bias toward mistakes that might block personal and organizational learning. This study presents an advanced measurement method to assess the bias of mistakes. The essence of it is the detection of the existing contradictions between attitude and behavior toward mistakes at the personal and organizational levels, as well as combined. This study is based on empirical evidence from a sample of 768 knowledge workers, divided into biased and non-biased subsamples following the procedure proposed in this paper. Those subsamples were next applied to the structural model, examining knowledge, learning, and collaboration cultures (the KLC approach) 's influence on organizational intelligence to validate the proposed method. Results showed that the applied method efficiently detects the DBM and exposes that in doubly mistakes-biased knowledge-driven organizations, the influence of knowledge culture on the mistakes acceptance component of learning culture is negative. So, organizations with a dominated double bias of mistakes do not accept the affirmation of learning from mistakes. Summing up, this study constitutes the Double Bias of Mistakes Theory, which states that the clash between positive attitudes and beliefs regarding learning processes and negative attitudes and beliefs toward mistakes exposed by focusing on control managers (bosses) might block organizational learning from mistakes and, as a consequence, negatively affect organizational intelligence. Without the empirical support for this theory, there was a risk that the idea of accepting mistakes as a potential source of learning would be simplified by biased minds to mistakes tolerance and rejected as ridiculous. Accepting that mistakes can be a source of precious learning does not equal mistake tolerance. On the contrary, it is the first step to managing mistakes and creating efficient error avoidance systems thanks to lessons learned from failures. This study introduces the method of measurement and detection of the Double Bias of Mistakes phenomenon, contributing to the science of organizational learning and collective intelligence-building.
{"title":"Double Bias of Mistakes: Essence, Consequences, and Measurement Method","authors":"W. Kucharska, A. Kopytko","doi":"10.34190/ejbrm.22.1.3320","DOIUrl":"https://doi.org/10.34190/ejbrm.22.1.3320","url":null,"abstract":"There is no learning without mistakes. However, there is a clash between ‘positive attitudes and beliefs’ regarding learning processes and the ‘negative attitudes and beliefs’ toward these being accompanied by mistakes. This clash exposes a cognitive bias toward mistakes that might block personal and organizational learning. This study presents an advanced measurement method to assess the bias of mistakes. The essence of it is the detection of the existing contradictions between attitude and behavior toward mistakes at the personal and organizational levels, as well as combined. This study is based on empirical evidence from a sample of 768 knowledge workers, divided into biased and non-biased subsamples following the procedure proposed in this paper. Those subsamples were next applied to the structural model, examining knowledge, learning, and collaboration cultures (the KLC approach) 's influence on organizational intelligence to validate the proposed method. Results showed that the applied method efficiently detects the DBM and exposes that in doubly mistakes-biased knowledge-driven organizations, the influence of knowledge culture on the mistakes acceptance component of learning culture is negative. So, organizations with a dominated double bias of mistakes do not accept the affirmation of learning from mistakes. Summing up, this study constitutes the Double Bias of Mistakes Theory, which states that the clash between positive attitudes and beliefs regarding learning processes and negative attitudes and beliefs toward mistakes exposed by focusing on control managers (bosses) might block organizational learning from mistakes and, as a consequence, negatively affect organizational intelligence. Without the empirical support for this theory, there was a risk that the idea of accepting mistakes as a potential source of learning would be simplified by biased minds to mistakes tolerance and rejected as ridiculous. Accepting that mistakes can be a source of precious learning does not equal mistake tolerance. On the contrary, it is the first step to managing mistakes and creating efficient error avoidance systems thanks to lessons learned from failures. This study introduces the method of measurement and detection of the Double Bias of Mistakes phenomenon, contributing to the science of organizational learning and collective intelligence-building.","PeriodicalId":38532,"journal":{"name":"Electronic Journal of Business Research Methods","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141118612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To date, there has been no proposed method to statistically validate Venn diagrams. We seek to correct this shortcoming. This paper is a review of a proposed method that offers the possibility of statistically validating Venn diagrams through the lens of the management vs. leadership debate in business. Through this research, we demonstrate a way to statistically validate Venn diagrams by using a modified method of exploratory factor analysis (EFA). First, when performing EFA to validate a Venn, we suggest the scree plot of eigenvalues will indicate how many circles should be in the diagram. Additionally, when normally conducting EFA, cross-loaded items are removed. However, when using EFA to validate a Venn, we propose items that cross load should be retained and placed in the corresponding intersection of the two (or more) circles of the diagram. Applying this method to a sample of 431 (n=431) employees aged 25 years or older, we created a statistically validated Venn diagram that identifies those skills that are uniquely management, uniquely leadership, and the overlap as reported by employees. As a result, this research provides scholars with the opportunity to classify actions as leadership or management based on their placement within the statistically validated Venn diagram of management skills and leadership skills. Importantly, through the application of this new research method, we bring the possibility of statistical confirmation to many of our social science theories that are represented by Venn diagrams. In the Discussion section, we offer a critique of possible limitations of the method and mistakes that researchers can make when applying this method.
{"title":"Statistically Validating a Theory Represented by a Venn Diagram","authors":"Crystal Evans, Gregory Evans, Lorin Mayo, Tammy Corcoran","doi":"10.34190/ejbrm.22.1.2966","DOIUrl":"https://doi.org/10.34190/ejbrm.22.1.2966","url":null,"abstract":"To date, there has been no proposed method to statistically validate Venn diagrams. We seek to correct this shortcoming. This paper is a review of a proposed method that offers the possibility of statistically validating Venn diagrams through the lens of the management vs. leadership debate in business. Through this research, we demonstrate a way to statistically validate Venn diagrams by using a modified method of exploratory factor analysis (EFA). First, when performing EFA to validate a Venn, we suggest the scree plot of eigenvalues will indicate how many circles should be in the diagram. Additionally, when normally conducting EFA, cross-loaded items are removed. However, when using EFA to validate a Venn, we propose items that cross load should be retained and placed in the corresponding intersection of the two (or more) circles of the diagram. Applying this method to a sample of 431 (n=431) employees aged 25 years or older, we created a statistically validated Venn diagram that identifies those skills that are uniquely management, uniquely leadership, and the overlap as reported by employees. As a result, this research provides scholars with the opportunity to classify actions as leadership or management based on their placement within the statistically validated Venn diagram of management skills and leadership skills. Importantly, through the application of this new research method, we bring the possibility of statistical confirmation to many of our social science theories that are represented by Venn diagrams. In the Discussion section, we offer a critique of possible limitations of the method and mistakes that researchers can make when applying this method.","PeriodicalId":38532,"journal":{"name":"Electronic Journal of Business Research Methods","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140234132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-19DOI: 10.34190/ejbrm.22.1.3212
Pierre Andrieux, Stephanie Leonard, Vanessa Simmering, Marcia Simmering, Christie Fuller
A growing body of academic research addresses issues related to questionable choices and errors in the use of research methods in published business research. These problematic research method practices (PRMPs) may be purposeful or unconscious, but they reduce the rigor of academic research and can harm the accumulation of scientific knowledge. Yet, absent from much of this literature is a theoretically grounded approach to understanding why these problematic practices occur. Prior scholars have summarized specific types of PRMPs, but attributions about their causes are primarily limited to research lack of motivation or poor doctoral education. While these may certainly be at play, the current manuscript proposes that the deeper psychological phenomenon of cognitive bias is a likely explanation. Cognitive biases occur when human cognition produces an outcome that is systematically distorted from objective reality (Haselton, Nettle, and Murray, 2016). More colloquially, cognitive biases are systematic errors that humans make when they are faced with perceiving, remembering, and understanding information. These unintentional biases are particularly likely when that information is voluminous and ambiguous. Cognitive biases are explained by two theories—heuristic theory and fuzzy trace theory. Heuristic theory suggests that humans default to using mental shortcuts as a means to make decisions more efficiently (Chaiken and Ledgerwood, 2012). Further, fuzzy trace theory explains how memory and reasoning can be flawed (Reyna and Brainerd, 1995). Because of the limitations of the human mind, heuristic theory and fuzzy trace theory act to create unintentional cognitive biases. The current manuscript argues that the cognitive biases of source confusion, gist memory, repetition effects, bandwagon effects, and confirmation bias are mostly subconscious means by which researchers make errors in research methods use. We argue that these biases are not a useful part of the didactic approach to research, but are rather mental shortcuts that can limit researcher effectiveness. Next, specific PRMPs are addressed: reliance on methodological myths and urban legends, errors in citations, use of questionable research practices, and inappropriate use of artificial intelligence (AI) tools and technology in research. Finally, there are a number of insights and recommendations derived from research on cognitive biases to assist scholars in promoting research methods best practices. In particular, researchers can combat cognitive biases by recognizing what they are and by providing more transparency about research methods use in their articles. Incentives for authors and reviewers may reduce the impact of cognitive biases on PRMPs. Editors should create and share clear guidelines on the use of AI in research. In summary, this manuscript addresses those critical issues, fills a gap in current research regarding why PRMPs occur, and provides researchers with key insights to
{"title":"How Cognitive Biases Influence Problematic Research Methods Practices","authors":"Pierre Andrieux, Stephanie Leonard, Vanessa Simmering, Marcia Simmering, Christie Fuller","doi":"10.34190/ejbrm.22.1.3212","DOIUrl":"https://doi.org/10.34190/ejbrm.22.1.3212","url":null,"abstract":"A growing body of academic research addresses issues related to questionable choices and errors in the use of research methods in published business research. These problematic research method practices (PRMPs) may be purposeful or unconscious, but they reduce the rigor of academic research and can harm the accumulation of scientific knowledge. Yet, absent from much of this literature is a theoretically grounded approach to understanding why these problematic practices occur. Prior scholars have summarized specific types of PRMPs, but attributions about their causes are primarily limited to research lack of motivation or poor doctoral education. While these may certainly be at play, the current manuscript proposes that the deeper psychological phenomenon of cognitive bias is a likely explanation. Cognitive biases occur when human cognition produces an outcome that is systematically distorted from objective reality (Haselton, Nettle, and Murray, 2016). More colloquially, cognitive biases are systematic errors that humans make when they are faced with perceiving, remembering, and understanding information. These unintentional biases are particularly likely when that information is voluminous and ambiguous. Cognitive biases are explained by two theories—heuristic theory and fuzzy trace theory. Heuristic theory suggests that humans default to using mental shortcuts as a means to make decisions more efficiently (Chaiken and Ledgerwood, 2012). Further, fuzzy trace theory explains how memory and reasoning can be flawed (Reyna and Brainerd, 1995). Because of the limitations of the human mind, heuristic theory and fuzzy trace theory act to create unintentional cognitive biases. The current manuscript argues that the cognitive biases of source confusion, gist memory, repetition effects, bandwagon effects, and confirmation bias are mostly subconscious means by which researchers make errors in research methods use. We argue that these biases are not a useful part of the didactic approach to research, but are rather mental shortcuts that can limit researcher effectiveness. Next, specific PRMPs are addressed: reliance on methodological myths and urban legends, errors in citations, use of questionable research practices, and inappropriate use of artificial intelligence (AI) tools and technology in research. Finally, there are a number of insights and recommendations derived from research on cognitive biases to assist scholars in promoting research methods best practices. In particular, researchers can combat cognitive biases by recognizing what they are and by providing more transparency about research methods use in their articles. Incentives for authors and reviewers may reduce the impact of cognitive biases on PRMPs. Editors should create and share clear guidelines on the use of AI in research. In summary, this manuscript addresses those critical issues, fills a gap in current research regarding why PRMPs occur, and provides researchers with key insights to ","PeriodicalId":38532,"journal":{"name":"Electronic Journal of Business Research Methods","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140450993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-13DOI: 10.34190/ejbrm.21.1.2903
Nompumelelo Monageng
Mixed methods research is not commonly adopted by researchers studying tax compliance behaviour despite the benefits that it can bring to research in this area. This is a method that is generally associated with social sciences however, this emergent methodology is being increasingly applied in disciplines that are traditionally associated with quantitative research, including in tax compliance research. Despite the growing trend in applying mixed methods to tax compliance research, there are no known studies that have summarised this methodological approach for researchers and provide guidance on how mixing research methods can allow for an in-depth view of tax compliance behaviour. The purpose of this article is first, to briefly explain mixed methods research for novice and established researchers unfamiliar with this methodological approach; second, provide an overview of the use of mixed methods in tax compliance research; third, provide an example of using mixed methods in order to illustrate a practical application of mixed methods; fourth, to discuss the value gained in applying mixed methods to examine and understand the effect of reciprocity nudges on tax compliance behaviour as well how challenges in applying mixed methods research can be faced. This article contributes to the business and management methodological literature by summarising the implementation of this approach and how studies aimed at understanding tax compliance behaviour could be enriched by embracing a mixed methods approach.
{"title":"Using Mixed Methods to Understand Tax Compliance Behaviour","authors":"Nompumelelo Monageng","doi":"10.34190/ejbrm.21.1.2903","DOIUrl":"https://doi.org/10.34190/ejbrm.21.1.2903","url":null,"abstract":"Mixed methods research is not commonly adopted by researchers studying tax compliance behaviour despite the benefits that it can bring to research in this area. This is a method that is generally associated with social sciences however, this emergent methodology is being increasingly applied in disciplines that are traditionally associated with quantitative research, including in tax compliance research. Despite the growing trend in applying mixed methods to tax compliance research, there are no known studies that have summarised this methodological approach for researchers and provide guidance on how mixing research methods can allow for an in-depth view of tax compliance behaviour. The purpose of this article is first, to briefly explain mixed methods research for novice and established researchers unfamiliar with this methodological approach; second, provide an overview of the use of mixed methods in tax compliance research; third, provide an example of using mixed methods in order to illustrate a practical application of mixed methods; fourth, to discuss the value gained in applying mixed methods to examine and understand the effect of reciprocity nudges on tax compliance behaviour as well how challenges in applying mixed methods research can be faced. This article contributes to the business and management methodological literature by summarising the implementation of this approach and how studies aimed at understanding tax compliance behaviour could be enriched by embracing a mixed methods approach.","PeriodicalId":38532,"journal":{"name":"Electronic Journal of Business Research Methods","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135734160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-17DOI: 10.34190/ejbrm.21.1.2933
R. Rodrigues, P. Lopes, Miguel Varela
The instruments that are constituted by inquiries that intend to investigate the opinions, behaviors and attitudes, instead of putting the person to the test, intend to find out how they would act in a given situation. Although there are no right or wrong answers, there is a tendency to respond in a socially acceptable way, even if the answer does not correspond to reality. This problem can be overcome through the Q-sort methodology that combines quantitative and qualitative data and analytical techniques that are not present in other methods. In this way, it consists of presenting the participants with a set of statements on a given topic and asking them to classify them according to their opinion, according to a predefined distribution, which is generally approximately normal. This methodology forces participants to distribute the score among the items on the scale, thus avoiding the constraints associated with social desirability and the tendency to respond in the same way or always through the midpoint to different questions. Another advantage is that it provides linearity and near-normality to the scale, which makes it possible to compare subjects more easily. Nevertheless, its advantages, Q-sort methodology also has negative points because forced-choice measures produce ipsative data that lead to distorted scales and problematic psychometric properties. As the data are obtained by ordering a set of items or by forcefully choosing one item over another, it is impossible to achieve very high or very low values on all scales, which gives rise to a large number of negative values that, in turn, result in an average correlation between the scales, which is also negative. In view of the above, it was considered relevant to apply the Q-sort methodology to a personality inventory, whose data were collected from 175 university students attending the Portuguese higher education institution which specializes in the area of economic and business sciences. The Q-sort methodology plays a crucial role in personality inventories by offering a subjective and personalized approach to assessing personality traits. It enables a more thorough and contextual analysis of individual traits, thereby contributing to a deeper and more comprehensive understanding of the human personality. The results of the empirical study showed that despite the mean values being negative or very close to zero, they allowed the grouping of respondents according to their similarities in terms of their personality traits depending on the course they attend.
{"title":"Q-Sort: A Blended Methodology Applied to a Personality Inventory","authors":"R. Rodrigues, P. Lopes, Miguel Varela","doi":"10.34190/ejbrm.21.1.2933","DOIUrl":"https://doi.org/10.34190/ejbrm.21.1.2933","url":null,"abstract":"The instruments that are constituted by inquiries that intend to investigate the opinions, behaviors and attitudes, instead of putting the person to the test, intend to find out how they would act in a given situation. Although there are no right or wrong answers, there is a tendency to respond in a socially acceptable way, even if the answer does not correspond to reality. This problem can be overcome through the Q-sort methodology that combines quantitative and qualitative data and analytical techniques that are not present in other methods. In this way, it consists of presenting the participants with a set of statements on a given topic and asking them to classify them according to their opinion, according to a predefined distribution, which is generally approximately normal. This methodology forces participants to distribute the score among the items on the scale, thus avoiding the constraints associated with social desirability and the tendency to respond in the same way or always through the midpoint to different questions. Another advantage is that it provides linearity and near-normality to the scale, which makes it possible to compare subjects more easily. Nevertheless, its advantages, Q-sort methodology also has negative points because forced-choice measures produce ipsative data that lead to distorted scales and problematic psychometric properties. As the data are obtained by ordering a set of items or by forcefully choosing one item over another, it is impossible to achieve very high or very low values on all scales, which gives rise to a large number of negative values that, in turn, result in an average correlation between the scales, which is also negative. In view of the above, it was considered relevant to apply the Q-sort methodology to a personality inventory, whose data were collected from 175 university students attending the Portuguese higher education institution which specializes in the area of economic and business sciences. The Q-sort methodology plays a crucial role in personality inventories by offering a subjective and personalized approach to assessing personality traits. It enables a more thorough and contextual analysis of individual traits, thereby contributing to a deeper and more comprehensive understanding of the human personality. The results of the empirical study showed that despite the mean values being negative or very close to zero, they allowed the grouping of respondents according to their similarities in terms of their personality traits depending on the course they attend.","PeriodicalId":38532,"journal":{"name":"Electronic Journal of Business Research Methods","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43736706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-14DOI: 10.34190/ejbrm.21.1.2627
M. Mkansi, Ntombi Mkalipi
The paper cogitates on the critical advent of 4th IR focusing on the concept of machine learning (ML) underpinned by natural language processing (NLP) to demonstrate how research philosophies and paradigms can be better taught and learned for students' benefit. A systematic literature review was earmarked for its depth and textual inquiry from scholarly arguments. The main purpose of this paper is to aver a progressive technological approach towards better comprehensive research paradigms and philosophies, which are complex domains with diverse variety in higher education and a cause of discomfort for students at post-graduate levels. Using quantitative algorithm, the natural language processing and machine learning-inspired digital model poses questions that place students in a reflexive mode and draws their articulated responses as inputs that model their worldviews against a host of philosophies in the database. The paper revealed that, discordant with previous scholars who advocated for a single philosophical assumption for a field, subject or researcher, such as the existence of a pure positivist and/ or pure interpretivist, purist philosophical assumptions should be challenged to benefit students and academics. It means that the digital discovery of research philosophies and paradigms extends the work of previous theorists to the technologically inspired discovery of episteme, ontology and axiology. By its nature, the use of NLP becomes an advanced channel on how we know what we know and the nature of the reality and values being displayed. The paper contributes to the evocation of deep learning arising from new philosophies and methods. The inquiry-based teaching approach transforms learning from the generic push-teaching method that assumes universality to the fostering of a reflexive approach that helps resolve the deep ideological approaches that caused the polarisation. The manner in which NLP and ML are able to extract information relevant to knowledge or philosophical discovery paves the way for approaches that can lead to the depolarisation and decolonisation of research philosophies, which can ultimately boost the development of research students.
{"title":"Natural Language Processing and Machine Learning Approach to Teaching and Learning Research Philosophies and Paradigms","authors":"M. Mkansi, Ntombi Mkalipi","doi":"10.34190/ejbrm.21.1.2627","DOIUrl":"https://doi.org/10.34190/ejbrm.21.1.2627","url":null,"abstract":"The paper cogitates on the critical advent of 4th IR focusing on the concept of machine learning (ML) underpinned by natural language processing (NLP) to demonstrate how research philosophies and paradigms can be better taught and learned for students' benefit. A systematic literature review was earmarked for its depth and textual inquiry from scholarly arguments. The main purpose of this paper is to aver a progressive technological approach towards better comprehensive research paradigms and philosophies, which are complex domains with diverse variety in higher education and a cause of discomfort for students at post-graduate levels. Using quantitative algorithm, the natural language processing and machine learning-inspired digital model poses questions that place students in a reflexive mode and draws their articulated responses as inputs that model their worldviews against a host of philosophies in the database. The paper revealed that, discordant with previous scholars who advocated for a single philosophical assumption for a field, subject or researcher, such as the existence of a pure positivist and/ or pure interpretivist, purist philosophical assumptions should be challenged to benefit students and academics. It means that the digital discovery of research philosophies and paradigms extends the work of previous theorists to the technologically inspired discovery of episteme, ontology and axiology. By its nature, the use of NLP becomes an advanced channel on how we know what we know and the nature of the reality and values being displayed. The paper contributes to the evocation of deep learning arising from new philosophies and methods. The inquiry-based teaching approach transforms learning from the generic push-teaching method that assumes universality to the fostering of a reflexive approach that helps resolve the deep ideological approaches that caused the polarisation. The manner in which NLP and ML are able to extract information relevant to knowledge or philosophical discovery paves the way for approaches that can lead to the depolarisation and decolonisation of research philosophies, which can ultimately boost the development of research students.","PeriodicalId":38532,"journal":{"name":"Electronic Journal of Business Research Methods","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43687176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-09DOI: 10.34190/ejbrm.21.1.2720
Samuel Reeb
The maturity model (MM) and Delphi research areas are extensive and diverse, leading to numerous approaches. This study addresses the Delphi method regarding its rigor requirements within the IS literature. To this end, the example of maturity model development is investigated. Hence, Delphi studies for MM development are identified and analyzed regarding their rigorous application and design. The examination focuses on the connections between maturity model aspects and the Delphi methodology. Hence, relevant aspects of maturity model and Delphi literature are elaborated, and criteria for methodological rigor are derived. A key challenge is linking the method to the specific design objective (in this study example, the development of a maturity model). After conducting a literature search to identify studies that use the Delphi method for MM development, these criteria are used as a basis for deductive content analysis. The results indicate a lack of clarity regarding the methodology, as different aspects are reported, although the general demands, starting points, and goals were similar. A need for design guidelines for planning and conducting Delphi studies is emphasized and addressed in this paper. Hence, guidelines for designing Delphi studies are developed and presented, considering relevant aspects for ensuring rigorous implementation. The focus lies on the linkage between study design and intended model elements, as this demonstrates the complexity of the study design and the relevance of the design decisions through an example. The guidelines integrate the different methodological aspects of maturity model development and the Delphi methodology, providing an orientation framework for the design process of such research projects. Therefore, this study contributes to existing research by proposing design guidelines for Delphi studies to foster rigor in the specific context of maturity model development. Although the presented guidelines focus on the maturity model context, the general design approach and decisions are transferable and applicable to other domains. Hence, this research contributes to the Delphi literature by providing insights into how relevant elements should be addressed in the designing process of a Delphi Study. Scholars should investigate how the presented guidelines must be adapted for other domains in future research.
{"title":"Towards Delphi Rigor: An Investigation in the Context of Maturity Model Development","authors":"Samuel Reeb","doi":"10.34190/ejbrm.21.1.2720","DOIUrl":"https://doi.org/10.34190/ejbrm.21.1.2720","url":null,"abstract":"The maturity model (MM) and Delphi research areas are extensive and diverse, leading to numerous approaches. This study addresses the Delphi method regarding its rigor requirements within the IS literature. To this end, the example of maturity model development is investigated. Hence, Delphi studies for MM development are identified and analyzed regarding their rigorous application and design. The examination focuses on the connections between maturity model aspects and the Delphi methodology. Hence, relevant aspects of maturity model and Delphi literature are elaborated, and criteria for methodological rigor are derived. A key challenge is linking the method to the specific design objective (in this study example, the development of a maturity model). After conducting a literature search to identify studies that use the Delphi method for MM development, these criteria are used as a basis for deductive content analysis. The results indicate a lack of clarity regarding the methodology, as different aspects are reported, although the general demands, starting points, and goals were similar. A need for design guidelines for planning and conducting Delphi studies is emphasized and addressed in this paper. Hence, guidelines for designing Delphi studies are developed and presented, considering relevant aspects for ensuring rigorous implementation. The focus lies on the linkage between study design and intended model elements, as this demonstrates the complexity of the study design and the relevance of the design decisions through an example. The guidelines integrate the different methodological aspects of maturity model development and the Delphi methodology, providing an orientation framework for the design process of such research projects. Therefore, this study contributes to existing research by proposing design guidelines for Delphi studies to foster rigor in the specific context of maturity model development. Although the presented guidelines focus on the maturity model context, the general design approach and decisions are transferable and applicable to other domains. Hence, this research contributes to the Delphi literature by providing insights into how relevant elements should be addressed in the designing process of a Delphi Study. Scholars should investigate how the presented guidelines must be adapted for other domains in future research.","PeriodicalId":38532,"journal":{"name":"Electronic Journal of Business Research Methods","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44742663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.34190/ejbrm.20.3.2579
Guillermo Navarro Sanfelix, Francisco Puig
In recent years, companies operating in activities such as dentistry, optometry, physiotherapy, or veterinary have seen the demand for their services grow. Their customers do not require their services only for health reasons but also for aesthetics and welfare issues. As a result, these companies compete in expanding and profitable markets. However, this business context has been detected by many professional entrepreneurs who decided to run their activity in healthcare and set up a firm without the necessary assets and knowledge. To overcome these liabilities, some seek partners who provide them with the resources they do not have by entering into different alliances. In contrast, others choose to compete under an independent business model. This paper sheds light on the factors influencing the decisions about the implemented business model in small knowledge-intensive firms by examining the association between the perception of the institutional environment variables and the dotation of intangible resources. For that purpose, a qualitative comparative analysis (QCA) was performed. Due to government regulations in force in these sectors, and methodological reasons, the study sample consisted of 88 small Spanish firms (less than 15 employees). The data were collected by a questionnaire distributed in 2017. We find that the choice to remain self-governing or to enter into a partnership (e.g franchising) is heterogeneously motivated by the evaluations that entrepreneurs have about the role of institutions concerning their activities and how high they consider their intellectual capital compared to their main competitors. In terms of institutional capital, these entrepreneurs refuse to implement patient loyalty policies and strive to have high-quality human capital in terms of the training & experience of their professionals. Moreover, the results also showed that independent business models pay little attention to market influences and view a certain level of regulation favorably, suggesting vocational and conservative behavior
{"title":"Knowledge-Intensive Business Services and Business Models: a Qualitative Comparative Analysis of Small Private Healthcare Providers","authors":"Guillermo Navarro Sanfelix, Francisco Puig","doi":"10.34190/ejbrm.20.3.2579","DOIUrl":"https://doi.org/10.34190/ejbrm.20.3.2579","url":null,"abstract":" In recent years, companies operating in activities such as dentistry, optometry, physiotherapy, or veterinary have seen the demand for their services grow. Their customers do not require their services only for health reasons but also for aesthetics and welfare issues. As a result, these companies compete in expanding and profitable markets. However, this business context has been detected by many professional entrepreneurs who decided to run their activity in healthcare and set up a firm without the necessary assets and knowledge. To overcome these liabilities, some seek partners who provide them with the resources they do not have by entering into different alliances. In contrast, others choose to compete under an independent business model. This paper sheds light on the factors influencing the decisions about the implemented business model in small knowledge-intensive firms by examining the association between the perception of the institutional environment variables and the dotation of intangible resources. For that purpose, a qualitative comparative analysis (QCA) was performed. Due to government regulations in force in these sectors, and methodological reasons, the study sample consisted of 88 small Spanish firms (less than 15 employees). The data were collected by a questionnaire distributed in 2017. We find that the choice to remain self-governing or to enter into a partnership (e.g franchising) is heterogeneously motivated by the evaluations that entrepreneurs have about the role of institutions concerning their activities and how high they consider their intellectual capital compared to their main competitors. In terms of institutional capital, these entrepreneurs refuse to implement patient loyalty policies and strive to have high-quality human capital in terms of the training & experience of their professionals. Moreover, the results also showed that independent business models pay little attention to market influences and view a certain level of regulation favorably, suggesting vocational and conservative behavior","PeriodicalId":38532,"journal":{"name":"Electronic Journal of Business Research Methods","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42073371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-28DOI: 10.34190/ejbrm.20.3.2503
B. Daniel
This article presents nine common challenges postgraduate students and early career academics face when engaging with academic literature. Data was collected from a sample of sixty-two postgraduate and early career academics who participated in a series of workshops on research methodology at a research-intensive university in New Zealand. Participants were invited to answer open-ended questions online about the purpose of undertaking a literature review and the challenges associated with the process. Findings revealed that participants held fragmented views about the purpose of engaging with the literature review, which contributed to the difficulties they faced in effectively undertaking the literature review. The challenges participants reported when undertaking literature reviews: difficulties in choosing a practical approach to reviewing the literature, inability to design an efficient search strategy to locate materials for review, problems locating relevant literature, an inability to determine the appropriate scope of a review, issues in choosing relevant materials and managing the growing volume of published work, problems in effectively synthesising and critiquing the literature, inability to organise and write clear reports, and lack of indicators for assessing the quality of written literature reports. The research presents a wide range of strategies students, and early career academics can use to mitigate these challenges. Teachers of research methods can also use these strategies to support students develop the necessary skills and knowledge to tackle the challenges of engaging with the literature.
{"title":"Common Challenges Postgraduate Students and Early-Career Academics face when Engaging with the Scholarly Literature","authors":"B. Daniel","doi":"10.34190/ejbrm.20.3.2503","DOIUrl":"https://doi.org/10.34190/ejbrm.20.3.2503","url":null,"abstract":"This article presents nine common challenges postgraduate students and early career academics face when engaging with academic literature. Data was collected from a sample of sixty-two postgraduate and early career academics who participated in a series of workshops on research methodology at a research-intensive university in New Zealand. Participants were invited to answer open-ended questions online about the purpose of undertaking a literature review and the challenges associated with the process. Findings revealed that participants held fragmented views about the purpose of engaging with the literature review, which contributed to the difficulties they faced in effectively undertaking the literature review. The challenges participants reported when undertaking literature reviews: difficulties in choosing a practical approach to reviewing the literature, inability to design an efficient search strategy to locate materials for review, problems locating relevant literature, an inability to determine the appropriate scope of a review, issues in choosing relevant materials and managing the growing volume of published work, problems in effectively synthesising and critiquing the literature, inability to organise and write clear reports, and lack of indicators for assessing the quality of written literature reports. The research presents a wide range of strategies students, and early career academics can use to mitigate these challenges. Teachers of research methods can also use these strategies to support students develop the necessary skills and knowledge to tackle the challenges of engaging with the literature.","PeriodicalId":38532,"journal":{"name":"Electronic Journal of Business Research Methods","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44819558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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